Predictive Biomarkers for Checkpoint Inhibitor Immune-Related Adverse Events.

Immune-checkpoint inhibitors (ICIs) are antagonists of inhibitory receptors in the immune system, such as the cytotoxic T-lymphocyte-associated antigen-4, the programmed cell death protein-1 and its ligand PD-L1, and they are increasingly used in cancer treatment. By blocking certain suppressive pathways, ICIs promote T-cell activation and antitumor activity but may induce so-called immune-related adverse events (irAEs), which mimic traditional autoimmune disorders. With the approval of more ICIs, irAE prediction has become a key factor in improving patient survival and quality of life. Several biomarkers have been described as potential irAE predictors, some of them are already available for clinical use and others are under development; examples include circulating blood cell counts and ratios, T-cell expansion and diversification, cytokines, autoantibodies and autoantigens, serum and other biological fluid proteins, human leucocyte antigen genotypes, genetic variations and gene profiles, microRNAs, and the gastrointestinal microbiome. Nevertheless, it is difficult to generalize the application of irAE biomarkers based on the current evidence because most studies have been retrospective, time-limited and restricted to a specific type of cancer, irAE or ICI. Long-term prospective cohorts and real-life studies are needed to assess the predictive capacity of different potential irAE biomarkers, regardless of the ICI type, organ involved or cancer site.

Prediction of Immune-Related Adverse Events Induced by Immune Checkpoint Inhibitors With a Panel of Autoantibodies: Protocol of a Multicenter, Prospective, Observational Cohort Study.

Introduction: Immune checkpoint inhibitor (ICI) therapy is markedly improving the prognosis of patients with several types of cancer. On the other hand, the growth in the use of these drugs in oncology is associated with an increase in multiple immune-related adverse events (irAEs), whose optimal prevention and management remain unclear. In this context, there is a need for reliable and validated biomarkers to predict the occurrence of irAEs in patients treated with ICIs. Thus, the main objective of this study is to evaluate the diagnostic performance of a sensitive routinely available panel of autoantibodies consisting of antinuclear antibodies, rheumatoid factor, and antineutrophil cytoplasmic antibodies to identify patients at risk of developing irAEs. Methods and Analysis: A multicenter, prospective, observational, cohort study has been designed to be conducted in patients diagnosed with cancer amenable to ICI therapy. Considering the percentage of ICI-induced irAEs to be 25% and a loss to follow-up of 5%, it has been estimated that a sample size of 294 patients is required to detect an expected sensitivity of the autoantibody panel under study of 0.90 with a confidence interval (95%) of no less than 0.75. For 48 weeks, patients will be monitored through the oncology outpatient clinics of five hospitals in Spain. Immune-related adverse events will be defined and categorized according to CTCAE v. 5.0. All the patients will undergo ordinary blood tests at specific moments predefined per protocol and extraordinary blood tests at the time of any irAE being detected. Ordinary and extraordinary samples will be frozen and stored in the biobank until analysis in the same autoimmunity laboratory when the whole cohort reaches week 48. A predictive model of irAEs will be constructed with potential risk factors of immune-related toxicity including the autoantibody panel under study. Ethics and Dissemination: This protocol was reviewed and approved by the Ethical Committee of the Basque Country and the Spanish Agency of Medicines and Medical Devices. Informed consent will be obtained from all participants before their enrollment. The authors declare that the results will be submitted to an international peer-reviewed journal for their prompt dissemination.